Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models

Author:

Belhechmi Shaima,Bin Riccardo De,Rotolo Federico,Michiels StefanORCID

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Reference38 articles.

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2. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Ser B Methodol. 1996; 58:267–88.

3. Tibshirani R. The Lasso Method for Variable Selection in the Cox Model. Stat Med. 1997; 16(4):385–95. https://doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3.

4. Meinshausen N, Bühhlmann P. High-dimensional graphs and variable selection with the Lasso. Ann Stat. 2006; 34(3):1436–62.

5. Zhao P, Yu B. On Model Selection Consistency of Lasso. J Mach Learn Res. 2006; 7:2541–63.

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